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Nick McClure
TensorFlow Machine Learning Cookbook
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1622196TensorFlow Machine Learning Cookbookhttps://www.gandhi.com.mx/tensorflow-machine-learning-cookbook-2/phttps://gandhi.vtexassets.com/arquivos/ids/335801/292664f7-a49f-4f2e-8289-b8586319d886.jpg?v=6383342936453300009011001MXNPackt PublishingInStock/Ebooks/<p><strong>Explore machine learning concepts using the latest numerical computing library TensorFlow with the help of this comprehensive cookbook</strong></p><h2>About This Book</h2><ul><li>Your quick guide to implementing TensorFlow in your day-to-day machine learning activities</li><li>Learn advanced techniques that bring more accuracy and speed to machine learning</li><li>Upgrade your knowledge to the second generation of machine learning with this guide on TensorFlow</li></ul><h2>Who This Book Is For</h2><p>This book is ideal for data scientists who are familiar with C or Python and perform machine learning activities on a day-to-day basis. Intermediate and advanced machine learning implementers who need a quick guide they can easily navigate will find it useful.</p><h2>What You Will Learn</h2><ul><li>Become familiar with the basics of the TensorFlow machine learning library</li><li>Get to know Linear Regression techniques with TensorFlow</li><li>Learn SVMs with hands-on recipes</li><li>Implement neural networks and improve predictions</li><li>Apply NLP and sentiment analysis to your data</li><li>Master CNN and RNN through practical recipes</li><li>Take TensorFlow into production</li></ul><h2>In Detail</h2><p>TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. Youll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning each using Googles machine learning library TensorFlow.</p><p>This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP.</p><p>Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.</p><h2>Style and approach</h2><p>This book takes a recipe-based approach where every topic is explicated with the help of a real-world example.</p>...1602248TensorFlow Machine Learning Cookbook9011001https://www.gandhi.com.mx/tensorflow-machine-learning-cookbook-2/phttps://gandhi.vtexassets.com/arquivos/ids/335801/292664f7-a49f-4f2e-8289-b8586319d886.jpg?v=638334293645330000InStockMXN99999DIEbook20179781786466303_W3siaWQiOiJmYTA5NzE3Ny1kODU5LTQ0YWYtODIwMi00MWZkNTljNzAwYmIiLCJsaXN0UHJpY2UiOjEwMDEsImRpc2NvdW50IjoxMDAsInNlbGxpbmdQcmljZSI6OTAxLCJpbmNsdWRlc1RheCI6dHJ1ZSwicHJpY2VUeXBlIjoiV2hvbGVzYWxlIiwiY3VycmVuY3kiOiJNWE4iLCJmcm9tIjoiMjAyNC0wNC0wOFQxNjowMDowMFoiLCJyZWdpb24iOiJNWCIsImlzUHJlb3JkZXIiOmZhbHNlfV0=9781786466303_<p><strong>Explore machine learning concepts using the latest numerical computing library TensorFlow with the help of this comprehensive cookbook</strong></p><h2>About This Book</h2><ul><li>Your quick guide to implementing TensorFlow in your day-to-day machine learning activities</li><li>Learn advanced techniques that bring more accuracy and speed to machine learning</li><li>Upgrade your knowledge to the second generation of machine learning with this guide on TensorFlow</li></ul><h2>Who This Book Is For</h2><p>This book is ideal for data scientists who are familiar with C or Python and perform machine learning activities on a day-to-day basis. Intermediate and advanced machine learning implementers who need a quick guide they can easily navigate will find it useful.</p><h2>What You Will Learn</h2><ul><li>Become familiar with the basics of the TensorFlow machine learning library</li><li>Get to know Linear Regression techniques with TensorFlow</li><li>Learn SVMs with hands-on recipes</li><li>Implement neural networks and improve predictions</li><li>Apply NLP and sentiment analysis to your data</li><li>Master CNN and RNN through practical recipes</li><li>Take TensorFlow into production</li></ul><h2>In Detail</h2><p>TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. Youll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning each using Googles machine learning library TensorFlow.</p><p>This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP.</p><p>Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.</p><h2>Style and approach</h2><p>This book takes a recipe-based approach where every topic is explicated with the help of a real-world example.</p>(*_*)9781786466303_<p><strong>Explore machine learning concepts using the latest numerical computing library TensorFlow with the help of this comprehensive cookbook</strong></p><h2>About This Book</h2><ul><li>Your quick guide to implementing TensorFlow in your day-to-day machine learning activities</li><li>Learn advanced techniques that bring more accuracy and speed to machine learning</li><li>Upgrade your knowledge to the second generation of machine learning with this guide on TensorFlow</li></ul><h2>Who This Book Is For</h2><p>This book is ideal for data scientists who are familiar with C or Python and perform machine learning activities on a day-to-day basis. Intermediate and advanced machine learning implementers who need a quick guide they can easily navigate will find it useful.</p><h2>What You Will Learn</h2><ul><li>Become familiar with the basics of the TensorFlow machine learning library</li><li>Get to know Linear Regression techniques with TensorFlow</li><li>Learn SVMs with hands-on recipes</li><li>Implement neural networks and improve predictions</li><li>Apply NLP and sentiment analysis to your data</li><li>Master CNN and RNN through practical recipes</li><li>Take TensorFlow into production</li></ul><h2>In Detail</h2><p>TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. Youll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning each using Googles machine learning library TensorFlow.</p><p>This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP.</p><p>Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.</p><h2>Style and approach</h2><p>This book takes a recipe-based approach where every topic is explicated with the help of a real-world example.</p>...9781786466303_Packt Publishinglibro_electonico_7db9d1d3-b994-3f0b-b71f-89abc36990ce_9781786466303;9781786466303_9781786466303Nick McClureInglésMéxicohttps://getbook.kobo.com/koboid-prod-public/packt-epub-568e3d48-e33f-4d3e-ab88-3cbc69ee0d63.epub2017-02-14T00:00:00+00:00Packt Publishing